Title :
Non-Intrusive Efficiency Determination of In-Service Induction Motors using Genetic Algorithm and Air-Gap Torque Methods
Author :
Lu, Bin ; Cao, Wenping ; French, Ian ; Bradley, Keith J. ; Habetler, Thomas G.
Author_Institution :
Eaton Corp., Milwaukee
Abstract :
In-service testing poses particular difficulties for experimentally determining induction machine efficiency. This paper focuses on non-intrusive methods for testing in-service machines and proposes a hybrid method based on the air-gap torque method and genetic algorithms. The proposed method has been verified from the experimental results from three induction motors rated at 7.5 hp, 100 hp and 225 kW. The overall efficiency estimation accuracy is approximately within 4-5% errors.
Keywords :
genetic algorithms; induction motors; torque motors; air gap torque methods; efficiency estimation accuracy; genetic algorithm; hybrid method; in service induction motors; induction machine efficiency; non intrusive methods; nonintrusive efficiency determination; power 225 kW; Air gaps; Circuit testing; Electrical resistance measurement; Genetic algorithms; Induction machines; Induction motors; Parameter estimation; Power generation; Stators; Torque measurement;
Conference_Titel :
Industry Applications Conference, 2007. 42nd IAS Annual Meeting. Conference Record of the 2007 IEEE
Conference_Location :
New Orleans, LA
Print_ISBN :
978-1-4244-1259-4
Electronic_ISBN :
0197-2618
DOI :
10.1109/07IAS.2007.186
